Use and meaning of a particular word or a phrase vary by several factors. Currently, several semantic analysis techniques use syntactic features and consider the semantic context of a given word to identify its word-sense using various statistical and supervised/semi-supervised machine learning techniques. However, none of these techniques consider domain-specific factors such as temporal, regional, cultural, and colloquial language variations; this could result in obtaining the wrong word-sense of a particular word or a phrase.